Abstract. At present the lightning flash density is a key input parameter to assess the risk of occurrence of a lightning strike in a particular region of interest. Since it is known that flashes tend to have more than one ground termination point on average, the use of ground strike point densities as opposed to flash densities is more appropriate. Lightning location systems (LLSs) do not directly provide ground strike point densities. However, ingesting their observations into an algorithm that groups strokes in respective ground strike points results in the sought after density value. The aim of this study is to assess the ability of three distinct ground strike point algorithms to correctly determine the observed ground-truth strike points. The output of the algorithms is tested against a large set of ground-truth observations taken from different regions around the world, including Austria, Brazil, France, Spain, South Africa and the United States of America. These observations are linked to the observations made by local LLSs in order to retrieve the necessary parameters of each lightning discharge and serves as inputs for the algorithms. It follows that all three of the algorithms perform well, with success rates up to about 90 % to retrieve the correct type of the strokes in the flash, i.e., whether the stroke creates a new termination point or follows a pre-existing channel. The most important factor that influences the algorithms' performance is the accuracy by which the strokes are located by the LLS. Additionally, it is shown that the strokes' peak current plays an important role, whereby strokes with a larger absolute peak current have a higher probability of being correctly classified compared to the weaker strokes.

中文翻译：

---

负向下的闪电中的全局地面打击点特性–第2部分：算法验证

摘要。目前，闪电密度是评估特定关注区域发生雷击风险的关键输入参数。由于已知闪光灯通常平均具有一个以上的接地端点，因此使用接地触点密度而不是闪光灯密度更为合适。雷电定位系统（LLS）不能直接提供地面触击点密度。但是，将他们的观察结果吸收到对各个地面打击点的笔划进行分组的算法中，将导致寻求的密度值。这项研究的目的是评估三种不同的地面打击点算法正确确定观察到的地面真相打击点的能力。该算法的输出经过对来自世界不同地区（包括奥地利，巴西，法国，西班牙，南非和美利坚合众国）的大量地面实况观测值进行测试。这些观察与本地LLS的观察相关联，以便检索每个雷电放电的必要参数，并用作算法的输入。由此可见，这三种算法均表现良好，成功率高达90％左右，可以检索闪光中正确的笔触类型，即笔触是创建新的终止点还是遵循预先存在的通道。影响算法性能的最重要因素是LLS确定笔划的准确性。此外，还显示了笔划